LinDaFIX – Linked Data for Fighting Inequality in Complex Societies

This project aims to propose a set of tools to facilitate the integration, enrichment and analysis of the data provided by the Department of Social Welfare of the Barcelona City Council. Our approach relies on semantic technologies, reasoning and machine learning to cross-reference different sources of information and discover relationships that probabilistically indicate which people are at risk of poverty and social exclusion.

The main development tasks correspond to our main concrete objectives: (1) a semantic model reflecting the concepts manipulated by the social services domain, including inequality indicators and mapping between the model and the concrete data, (2) a semantic exploration and query tool, and (3) probabilistic prediction models of vulnerability and identification of citizens at risk.

The image of the project has all rights reserved to its author Antony Theobald.